Detailed analysis of the prediction accuracies of the test sets. Table S6. Percent of proteins in the test sets having âĽ30% sequence identity to those in pre-training/whole benchmark dataset and the prediction accuracy. Figure S5. Relationship between the prediction accuracy and the percent of proteins in a test set with âĽ30% sequence identity to those in the training set. (DOCX 105 kb
Improving accuracy of protein-protein interaction prediction by considering the converse problem for...
Text file contains the predicted results on the prediction set consisting of randomly sampled non-in...
Table S1. The AUCs of using CNNs with sequence and structure information for different hyperparamete...
Detailed description of the parameter selection. Figure S3. The 10-CV training accuracies of the pre...
Appendix with Supplementary Material. Appendix, including text, tables, and figures for supplementar...
Background: Protein-protein interactions (PPIs) are critical for many biological processes. It is th...
It contains five folders: 1). PDB. Crystallographic structures of TM proteins in the TrainData, Inde...
Table S1. The 31 informative physicochemical properties and their corresponding MED (main effect dif...
Figure S2. Performance of our approach as a function of different parameters: a) Query length – Perf...
local_feature_training_set.csv: Preprocessing data of feature extractor contains 65869 rows and 344 ...
Background: Protein-protein interactions underlie many important biological processes. Computational...
Detailed Experimental settings. Protein complex prediction for large protein protein interaction net...
Statistics for the number of truly predicted RNA-binding residues (nTPs) only by one prediction mode...
Figure S3. The normalized fold frequency of correct vs. incorrect associations for the assessment da...
Figure S3. The difference of predictive performance using sequence + structure and only sequence. On...
Improving accuracy of protein-protein interaction prediction by considering the converse problem for...
Text file contains the predicted results on the prediction set consisting of randomly sampled non-in...
Table S1. The AUCs of using CNNs with sequence and structure information for different hyperparamete...
Detailed description of the parameter selection. Figure S3. The 10-CV training accuracies of the pre...
Appendix with Supplementary Material. Appendix, including text, tables, and figures for supplementar...
Background: Protein-protein interactions (PPIs) are critical for many biological processes. It is th...
It contains five folders: 1). PDB. Crystallographic structures of TM proteins in the TrainData, Inde...
Table S1. The 31 informative physicochemical properties and their corresponding MED (main effect dif...
Figure S2. Performance of our approach as a function of different parameters: a) Query length – Perf...
local_feature_training_set.csv: Preprocessing data of feature extractor contains 65869 rows and 344 ...
Background: Protein-protein interactions underlie many important biological processes. Computational...
Detailed Experimental settings. Protein complex prediction for large protein protein interaction net...
Statistics for the number of truly predicted RNA-binding residues (nTPs) only by one prediction mode...
Figure S3. The normalized fold frequency of correct vs. incorrect associations for the assessment da...
Figure S3. The difference of predictive performance using sequence + structure and only sequence. On...
Improving accuracy of protein-protein interaction prediction by considering the converse problem for...
Text file contains the predicted results on the prediction set consisting of randomly sampled non-in...
Table S1. The AUCs of using CNNs with sequence and structure information for different hyperparamete...